In addition to fulfilling basic needs in the historical process, purchasing behavior has been based on many different sources of motivation, such as people’s desire to be liked, the need to be popular, the desire to show their status, and imitation (Bozdağ & Alkar, 2018). In today’s modern world, technological developments and the internet play an undeniable role in triggering the consumption frenzy. Shopping has taken its place in life as a phenomenon that ensures the satisfaction of desires, wishes, and impulses by going beyond being a way of meeting needs. In addition to the easy accessibility of online shopping, the fact that the perception of consumption is included in life through the relevant stimuli with the advancing technology can also be considered a predictor of consumption. Advertising and marketing strategies increase consumption by triggering individuals’ consumption perception and keeping their desire to be special alive through the messages given. Particularly, the concept of brand, which is an indicator of status, can be considered as shopping done to increase self-esteem through brands, to determine one’s social position, and to protect this position (Kadıoğlu, 2014; Neuner et al., 2005). The individual’s development of addiction by turning purchasing behavior and consumption into a compulsive action creates problematic online shopping behavior by evolving into today’s conditions and gaining momentum as a result of the conveniences provided by the online environment (Rose & Dhandayudham, 2014). Although it differs from other addictions at some points, the increasing perception of consumption indicates the necessity of studying online shopping addiction in clinical and social terms (Neuner et al., 2005). Online shopping addiction, which activates the reward center of the brain as in substance and gambling addiction and is included in the addiction cycle in terms of behavioral symptoms, is mentioned in the Diagnostic and Statistical Manual of Mental Disorders (DSM-V). According to the DSM-V, online shopping addiction, which is evaluated under the subheading “non-substance-related disorders” under the main heading “substance-related and addictive disorders,” is defined by behavioral patterns such as online gaming behavior, but shopping addiction is not referred to as the main heading. The conceptualization of online shopping addiction as a formal diagnosis has been challenged by some researchers. They argue that the justification for this categorization is undermined by the scarcity of published scientific literature, notably in the domains of neurobiology and genetics (Grant & Chamberlain, 2016; Grant et al., 2014). Nevertheless, online shopping addiction has been consistently linked to adverse psychological and neuropsychological outcomes in numerous studies (Claes et al., 2018; Kyrios et al., 2018; Trotzke et al., 2017). Therefore, it is clear that the relevant literature needs studies based on these issues.

In the case of online shopping addiction, the individual performs excessive spending behavior online by creating a response to the emotional, social, or economic problems he/she is experiencing through his/her online purchases. The most attractive aspect of online shopping addiction for individuals is that it is accessible regardless of time and place (Zhao et al., 2017). It is seen that shopping addiction, which is often attempted to be explained by compulsive purchasing behavior, does not attract attention only with its compulsive structure nowadays (American Psychiatric Association, 2013; Wolfinbarger & Gilly, 2001). There are many different points on which individuals’ shopping addiction is based. The most common psychopathological factors are impulse control disorder (Grant et al., 2005), substance use disorder (Grant et al., 2005), mood disorders (Mueller et al., 2007), eating disorders (Mueller et al., 2007), and narcissistic personality disorder (Rose, 2007). At this point, it would be appropriate to review the concept of narcissism.

In its most general definition, narcissism is considered a self-centered trait that involves receiving love from an object (Russell, 1985). According to the DSM-V, narcissism is defined as a behavioral pattern that begins in early adulthood with at least five or more of the following behaviors, appears in different contexts, and continues with the need for grandiosity and being liked (American Psychiatric Association, 2013).

  • An individual behaves proudly (exaggerates his/her achievements and talents).

  • An individual dreams of unlimited success, intelligence, power, beauty, or supreme love.

  • An individual believes that he/she is a special and superior person and that he/she will only be understood by special and superior people like himself/herself.

  • Being liked is highly desired.

  • An individual feels that he/she deserves what he/she wants.

  • An individual uses others for his/her own interests.

  • An individual does not have empathy (does not want to understand the feelings, thoughts, and needs of others).

  • An individual thinks others are jealous of him/her or rarely envies others.

  • He/she treats others with disrespect and exhibits a smug attitude.

Narcissism, which is evaluated as a dynamic whole, is organized with cognitive and emotional processes that affect interpersonal relationships. The individual has a structure of self with which he/she cannot progress healthily in his/her relationships with others due to deficiencies in both emotions and self-regulation skills. This structure is accompanied by the lack of impulse control and the perception of being entitled to reach pleasure instantly (Hepper et al., 2014). Self-regulation ability is considered a source of motivation that predicts the steps of individuals to meet their needs as well as building and maintaining their ideal self. The individual agrees that he/she should have every tangible or intangible object with good and desirable qualities (Jonason & Krause, 2013). The height of social status is important for a narcissistic individual. Just as he/she makes an effort to have an appearance that suits his/her status (Twenge and Campell, 2010), his/her exaggerated self-confidence and inflated self-perception are effective in the process (Raskin & Terry, 1988). It is assumed that the narcissistic individual’s desire to receive the approval and praise of others, to be appreciated, and to have the best and the most beautiful may be closely associated with brands (Twenge and Campbell, 2010). Therefore, it is clear that brands shape social status when it comes to shopping, and the desirability level of the rare is considered an element that attracts narcissistic individuals. Meanwhile, it is seen that compulsive purchasing behavior accompanying narcissistic personality disorder also develops (Schlosser et al., 1994). Here, the effects of impulse control disorder, which is frequently observed in narcissism, are also emphasized in the literature, whereas the relationship between narcissism, compulsive purchasing behavior, and impulse control disorder is mentioned (Rose & Dhandayudham, 2014).

As is seen, it is stated in the literature that narcissism may theoretically affect online shopping addiction. It is seen that narcissistic individuals exhibit high rates of consumption impulse, which is described as an addiction. It is expressed that materialism, which is considered a result of narcissism, triggers shopping addiction. It is mentioned that narcissistic individuals’ impulsivity and tendency to prefer short-term gains to long-term losses also affect the process. The fact that advertising and marketing strategies focus on the concepts of “live the moment” and “do not postpone pleasure,” in addition to putting emphasis on “feel special,” which attracts narcissistic individuals, also affects narcissistic individuals (Kadıoğlu, 2014; Twenge & Campbell, 2010). Furthermore, some demographic characteristics that affect online shopping addiction are also mentioned in the literature. Among these, age and gender come first. It is stated that age is negatively correlated with online shopping addiction (Manchiraju et al., 2017; Mikolajczak-Degrauwe et al., 2012). This is similar in narcissism. Narcissistic personality traits tend to decrease with advancing age (Foster et al., 2003). Moreover, studies focus on the fact that women are more addicted to online shopping than men (Neuner et al., 2005). However, in narcissism, this situation manifests itself in the opposite way. In other words, men exhibit more narcissistic behaviors than women (Grijalva et al., 2015; Jonason & Krause, 2013; Kaya & Kalkan, 2019; Kim & Jang, 2018; Köksal, 2020). In this case, when the gender, age, and narcissism levels of individuals are considered together, it is important to determine how online shopping addiction will be influenced. For this reason, it was decided that the exhaustive chi-squared automatic interaction detector (CHAID) analysis, which is used to determine the independent variables related to the dependent variable, would be a powerful method for determining the variables related to online shopping addiction. The prominent features of the exhaustive CHAID analysis and its significant use in this research can be listed as follows (Kass, 1980; Kayri & Boysan, 2007; Thomas & Galambos, 2004):

  • It determines the factors that most significantly affect the dependent variable.

  • Since it works by dividing heterogeneous groups into homogeneous subgroups, the homogeneity condition can be provided.

  • Many assumptions, such as normality in parametric tests, do not need to be met in the CHAID analysis.

  • Both categorical and continuous variables can be included in the model.

  • The rate of identifying risk factors is high in the CHAID analysis.

Considering all these, the present study aims to investigate the effect of narcissism, age, and gender on online shopping addiction by the exhaustive CHAID analysis. Answers to the following research questions are sought in line with the study’s purpose:

  1. 1.

    What is the distribution of the participants’ online shopping addiction and narcissism levels?

  2. 2.

    How are narcissism, gender, and age related to online shopping addiction?

Method

Research Design

Among quantitative research approaches, survey and correlational research will be used in the study. Survey research aims to determine the characteristics of participants regarding a subject or a phenomenon (online shopping addiction and narcissism levels); correlational research aims to investigate the relationship between two or more variables (the relationship between online shopping addiction and narcissism and demographic characteristics) (Fraenkel et al., 2012).

Participants

A total of 1018 adults aged 18 and above participated in the research, recruited online through convenience sampling methods. Participants provided informed consent by signing a consent form prior to voluntarily participating in the research. The study received ethics committee approval from a state university in Turkey to administer the scales used in the research. In the process of data preparation for analysis, extreme values were removed from the data set, and analyses were conducted with 1010 participants. Table 1 contains the demographic information of the participant group.

Table 1 Demographic information of the participants
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Data Collection Tools

The following scales were used as data collection tools in the study. The Online Shopping Addiction Scale (OSAS) developed by Zhao et al. (2017) was used to reveal the online shopping addiction levels of the participants. The Narcissism Scale (NS), a subscale of the Dark Triad Scale developed by Jones and Paulhus (2014), was employed to determine the levels of narcissism. The Personal Information Form was used to determine the participants’ demographic characteristics. Turkish validity and reliability studies of the scales to be used in the research were performed. The research data were collected online.

Validity and Reliability Studies of the OSAS

The OSAS, consisting of six factors and 18 items, has a 5-point Likert-type structure, ranging from the “I Strongly Disagree” option to the “I Strongly Agree” option. Zhao et al. (2017) calculated the internal consistency coefficient (α) for the OSAS as 0.95. The α values of the factors range between 0.71 and 0.84. Confirmatory factor analysis (CFA) was conducted with 946 participants to determine that the OSAS yielded valid results in the present study as well. The objective of CFA is to investigate the associations between a predetermined set of observed (measured) variables and underlying latent constructs (Tabachnick & Fidell, 2012). The CFA analysis was conducted using the Jamovi software program.

To assess reliability, the α value was calculated separately for the overall scale and factors. For α, these values are expected to be above 0.70. According to the analysis results, α was found to be within the accepted ranges in the literature (αOSAS = 0.95, αsalience = 0.79, αtolerance = 0.85, αmood = 0.94, αwithdrawal = 0.86, αrelapse = 0.88, αconflict = 0.83) (Nunnally & Bernstein, 1994). Table 2 contains the values obtained. The α value was calculated using the SPSS program.

Table 2 Reliability and item loading values related to the OSAS
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Upon examining the loading values of the items in the scale in addition to α in reliability assessment, it is observed that the values are in appropriate ranges (> 0.32) and statistically significant (Tabachnick & Fidell, 2012). Accordingly, reliability can be said to be provided at the item level.

Whether the scale was confirmed with the fit values obtained via CFA was checked. The analysis results revealed that the fit values (SRMR = 0.055, RMSEA = 0.079, NFI = 0.94, TLI = 0.93, CFI = 0.95) were appropriate in terms of the value ranges recommended in the literature. If χ2/sd = 6.95, it is not in the fit value range. However, Brown (2015) asserts that the χ2/sd value is very sensitive to the sample size. Considering that the data set comprised the data of 946 participants, this situation can be said to be negligible. Table 3 presents the obtained fit values.

Table 3 CFA fit values (OSAS)
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According to all the findings concerning the adaptation studies of the OSAS, the scale was found to be a valid and reliable measurement tool for the sample of this research.

Validity and Reliability Studies of the NS

The Narcissism Scale consists of one factor and nine items, and the α value calculated by Jones and Paulhus (2014) is 0.71. CFA was carried out and the α value was calculated to determine whether the scale yielded valid and reliable results for the sample of this study (Table 4).

Table 4 Reliability and item loading values related to the NS-1
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When the loading values of the items in the scale are examined, it is seen that the values except for the sixth item are in appropriate ranges (> 0.32) and statistically significant (Tabachnick & Fidell, 2012). The sixth item (I feel shy when someone compliments me) could not provide item-level reliability with an item load of 0.109. Hence, this item, which posed a problem in terms of validity and reliability, was removed, and CFA was repeated over eight items (Table 5).

Table 5 Reliability and item loading values related to the NS-2
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According to Table 5, the loading values of all items are in the appropriate range. The α value of 0.70 shows that the scale is reliable. It was examined whether the scale was confirmed with the fit values obtained from CFA. The analysis results indicated that the fit values (χ2/sd = 4.10, SRMR = 0.040, RMSEA = 0.056, NFI = 0.93, TLI = 0.93, CFI = 0.95) were appropriate in terms of the value ranges recommended in the literature. Table 6 presents the obtained fit values.

Table 6 CFA fit values (NS)
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According to all the findings regarding the adaptation studies of the NS, the scale was determined to be a valid and reliable measurement tool for the sample of this research.

Data Analysis

Descriptive statistics were used to answer the research question aiming to examine the online shopping addiction and narcissism levels of the participants, and the exhaustive chi-squared automatic interaction detector (exhaustive CHAID) method was employed to answer the research question aiming to reveal the effect of narcissism and demographic characteristics on online shopping addiction. Decision tree analysis determines the independent variables related to the dependent variable using the CHAID chi-square statistics (Agresti, 1990). In general, decision trees are analyses that gradually divide independent variables into groups (Kayri & Boysan, 2007) and model the interaction of independent variables that display the highest correlation with the dependent variable by establishing various iteration algorithms in each branch of the tree divided (Michael & Gordon, 2004). The functioning of the CHAID analysis begins after independent variables that have a significant correlation with the dependent or target variable are found. Afterward, category groupings are evaluated to select the most significant combination. The categories of the independent variable are combined if they are homogeneous when compared to the dependent variable. The independent variable with the strongest correlation with the target variable becomes the first branch in the tree with a leaf for each category that is significantly different from the outcome variable. The procedure is repeated to find the predictor variable that is most significantly related to the outcome variable on each leaf until no significant predictor remains (Thomas & Galambos, 2004).

Exhaustive CHAID is a CHAID modification that investigates all possible splits for each predictor. Exhaustive CHAID was proposed by Biggs et al. (1991) to eliminate the weaknesses of CHAID. At this point, weakness means that the CHAID algorithm stops working when the categories are found to be significantly different. Exhaustive CHAID, on the other hand, continues to combine predictor variables until only two categories remain. Moreover, it is preferred if there are missing values in the data set. Considering all these explanations, it was deemed appropriate to use the exhaustive CHAID analysis in answering the fourth question of the study.

Results

A general description of the online shopping addiction and narcissism levels of the participants was made by calculating the mean score obtained from the OSAS and NS and standard deviation (Table 7). The scores received by the participants from the factors of the OSAS are listed from higher to lower as Tolerance, Salience, Mood modification, Withdrawal, Relapse, and Conflict. The average online shopping addiction level of the participants is 2.01. This score can be at least 1 and at most 5. Therefore, it can be said that the participants display low levels of online shopping addiction. In the study, the average of narcissism was calculated as 2.89. Considering that this value may be between 1 and 5, it is seen that the participants have moderate levels of narcissism.

Table 7 Descriptive statistics regarding online shopping addiction and narcissism levels
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To reveal the relationship between online shopping addiction, narcissism, and demographic variables, the scores obtained from the OSAS were determined as dependent variables, and the scores obtained from the NS, age, and gender were determined as independent variables. The correlations between the relevant variables were analyzed by the exhaustive CHAID analysis (Fig. 1). It is observed that the variable with the highest correlation with online shopping addiction is age. Based on the age variable, the participants’ OSAS scores are clustered within four groups. Accordingly, the participants who are 26 years old or younger display the highest level of online shopping addiction (x = 2.249). The participants between the ages of 26 and 42 exhibit a lower level of addiction (x = 1.964), and the participants older than 42 have the lowest level of addiction (x = 1.633). The difference between these three groups was determined to be statistically significant (F(2,1007) = 48.899; p = 0.000).

Fig. 1
figure 1

Exhaustive CHAID analysis aiming to determine the correlation between online shopping addiction, narcissism, and demographic variables

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Upon examining the nodes in the second row, gender is seen to be the most important variable correlating the online shopping addiction of the participants under the age of 26 (F(1,394) = 24.323; p < 0.000). Accordingly, the level of online shopping addiction of the female group consisting of 276 individuals (x = 2.379) is significantly higher compared to the male group consisting of 120 individuals (x = 1.951). According to the nodes in the second row, narcissism is the most effective variable on the online shopping addiction of the participants between the ages of 26–42 (F(1,409) = 22.269; p = 0.000). Accordingly, the participants with an average of narcissism higher than 3.00 (x = 2.183) have higher online shopping addiction compared to individuals with an average of 3.00 and lower (x = 1.851). The variable that related to the online shopping addiction of the participants over the age of 42 in the nodes in the second row was narcissism (F(1,201) = 14.440; p = 0.009). Accordingly, the participants with an average of narcissism higher than 2.75 (x = 1.823) have significantly higher online shopping addiction than individuals with an average of 2.75 and lower (x = 1.493).

According to the nodes in the third row, it was elucidated that narcissism was the most important variable related to online shopping addiction of women younger than 26 years of age. Here, the exhaustive CHAID analysis formed three groups. In women younger than 26 years of age, the highest shopping addiction was observed in those with a level of narcissism higher than 3.00 (x = 2.579). Online shopping addiction is lower in those with narcissism levels between 2.50 and 3.00 (x = 2.357). Finally, the lowest level of online shopping addiction (x = 2.007) determined in women under the age of 26 is those with a narcissism level below 2.50. The averages of online shopping addiction between these three groups were statistically significant (F(2,273) = 11.440; p = 0.001). According to the nodes in the third row, gender is the variable that most relates to the online shopping addiction of participants over the narcissism level 3.00. Women (x = 1.984) have significantly higher online shopping addiction than men (x = 1.729) (F(1,270) = 11.538; p = 0.001).

To summarize the exhaustive CHAID analysis, it can be stated that the most important variable related to online shopping addiction is age, whereas gender and narcissism level are the most effective variables for online shopping addiction following age-related groupings. When the nodes in Fig. 1 are examined in ascending order, it can be seen that the group with the highest online shopping addiction is female participants (x = 2.579) who are under 26 years of age and whose narcissism levels are higher than 3.00.

Discussion

According to the results obtained from the study, the average of the online shopping addiction level of the participants was found to be 2.01, and the average of narcissism was found to be 2.89. Considering that the scores that can be obtained from the OSAS and NS may be between 1 and 5, it is seen that the participants have low levels of online shopping addiction and moderate levels of narcissism. The study by Yılmaz (2023) examining the correlation between online shopping addiction and life satisfaction revealed that the level of compulsive online purchases of 150 female students was low. In the study by Zhang et al. (2019), the majority of the participants had online shopping addiction. In this respect, it can be said that there are aspects of the research that are supported and not supported by the literature.

According to the results of the exhaustive CHAID analysis, it was revealed that the variable displaying the highest correlation with online shopping addiction was age. Based on the age variable, the participants’ OSAS scores are clustered within four groups. Accordingly, individuals who are 26 years old or younger exhibit the highest online shopping addiction, whereas this group is followed by participants aged 26–42 years, and older than 42 years, respectively. In other words, it was concluded that the levels of online shopping addiction decreased with the increasing age of the participants. In the literature, it has been reported that there is a negative correlation between individuals’ online shopping addiction and age (Armağan & Temel, 2018; Bozyel, 2020; Yılmaz, 2023). A study conducted by Topçuoğlu (2022) examined the impulsivity levels according to the age variable and concluded that the impulsivity levels of the participants under the age of 30 were higher than those of the participants over the age of 30. When the literature is reviewed, there are studies demonstrating that impulsivity and problematic online shopping behavior are related. For example, in the study by Flight and Scherle (2013), a positive correlation was found between problematic shopping behavior and impulsivity, and problematic shopping behavior increased with the increasing impulsivity level. Likewise, there are studies indicating that problematic shopping behavior increases due to the lack of impulse control and the perception of the right to instant gratification (Hepper et al., 2014). The study by Bozdağ Türker, (2019) found a statistically significant positive correlation between compulsive online purchasing behavior and impulsivity. Meanwhile, there are studies in the literature showing a correlation between impulse control disorders and problematic shopping behavior (Andreassen et al., 2015; DeSarbo & Edwards, 1996; Ghaseminejad & Nayebzadeh, 2017; Mowen & Spears, 1999; Müller et al., 2014; Otero-López & Villardefrancos, 2014; Ridgway et al., 2008; Wang & Wallendorf, 2006). Therefore, it can be said that impulsivity and indirectly online shopping addiction decrease with increasing age.

The fact that online shopping addiction is inversely proportional to age can also be interpreted as an increase in online shopping behaviors of young individuals since they spend more time online. Many studies have concluded that young people spend more time on the internet than adults. As a result, they are more addicted to the internet (Ferraro et al., 2006; Servidio, 2014; Young & Rogers, 1998). In their study, Sharif and Khanekharab (2017) and Sharif and Yeoh (2018) revealed that excessive internet use led to more problematic online shopping behavior in young individuals. In their study, Armağan and Temel (2018) also concluded that the compulsive shopping behavior tendencies of the participants who spent a long time on the internet increased. The study by Bozyel (2020) reported that purchasing behavior increased with an increase in the time spent on the internet. Likewise, Lee et al. (2016) concluded that there was a positive correlation between compulsive buying behavior and internet addiction in individuals who shopped online, and this might be related to the time spent online. At this point, it can be concluded that internet usage time and internet addiction decrease with advancing age, which reduces online shopping addiction behavior. Furthermore, it can be thought that individuals are more exposed to different advertisements, various advantages, and attractive prices of shopping sites when they use the internet for a long time and thus tend to shop more frequently.

When the following nodes were examined in the exhaustive CHAID analysis, it was determined that the most important variable correlating the online shopping addiction of the participants under 26 years of age was gender. Accordingly, the level of online shopping addiction of women under 26 years of age is higher than that of men in the same age groups. In the literature, there are findings indicating that women are more prone to shopping addiction than male users (Maraz et al., 2016; Rose & Dhandayudham, 2014; Zhang et al., 2019). The study by Koran et al. (2006) asserted that the rate of problematic shopping behavior in society was higher in women than in men. These results support the research result. In another study supporting the study result, the difference between the purchasing tendencies of female and male participants was investigated, and the purchasing tendencies of female participants were observed to be high (Neuner et al., 2005). Similarly, as a result of the study on problematic shopping behavior, Black (2001) indicated that 75–95% of individuals with problematic shopping behavior were women. Granero et al. (2016) also stated that problematic shopping behavior was more common in women than in men.

The results of the exhaustive CHAID analysis showed that narcissism was another important variable relating to online shopping addiction. Accordingly, the online shopping addiction of all participants between the ages of 26–42, and over 42 years, female participants under 26 years of age are directly proportional to narcissism. Participants with higher levels of narcissism in all three groups display more online shopping addiction. Yılmazoğlu (2018) concluded that consumers with narcissistic personality traits constantly exhibit shopping behavior to engage in a different thought and avoid problematic situations in addition to not being able to provide self-control and behaving impulsively. In the literature, there are also studies that have found a correlation between problematic shopping behavior and impulsivity, in addition to the correlation between narcissism and impulsivity (Flight & Scherle, 2013; Malesza & Kaczmarek, 2018). These findings coincide with the results of the research. However, this study determined that narcissistic traits were effective in online shopping addiction when the participants were grouped according to gender and age. Thus, it is also important to review studies related to narcissism, age, and gender variables.

Considering the correlation between narcissistic personality traits and gender, it is seen that male individuals often have higher levels of narcissism (Çakır, 2018; Grijalva et al., 2015; Jonason & Krause, 2013; Kaya & Kalkan, 2019; Kim & Jang, 2018; Köksal, 2020). Moreover, Okumuş (2020) revealed a decrease in narcissism tendencies with advancing age in young adults. Foster et al. (2003) addressed the correlation between narcissistic personality traits and age and observed that narcissistic traits decreased with advancing age. However, in this study, the group with the highest online shopping addiction was the youngest female participants with high levels of narcissism. With the increase in narcissistic behavior, online shopping addiction also increases. However, men are the group with a high tendency toward narcissism, in line with the literature. Furthermore, age and narcissistic behavior levels are inversely proportional in the literature. When all variables are examined together, there are aspects of the research that overlap with the literature, but there are also aspects that differ. Thus, the research expands the literature. According to all results, the need to conduct research by taking into account the level of narcissism, gender, and age of individuals together emerges.

Conclusion and Implications

In the study, the effect of narcissism, age, and gender on online shopping addiction was investigated by the exhaustive CHAID analysis. One thousand and ten adult individuals participated in the study, and the data were collected with the OSAS and NS, whose validity and reliability studies were reported in the method section. As a result of analyzing the data obtained, it was seen that the participants had low levels of online shopping addiction and moderate levels of narcissism. The variables that displayed the highest correlation with online shopping addiction were age, gender, and narcissism level, respectively. The results showed that the group with the highest online shopping addiction was female participants younger than 26 years of age with relatively high levels of narcissism. The results were discussed on the basis of the literature, and despite the presence of studies with similar results, it was found that this study made unique contributions to the literature by grouping individuals according to age, gender, and narcissism level. It is reported in the literature that narcissism is more common in men and younger individuals. However, one of the most important results of the study is that, in this study, individuals with online shopping addiction are mostly relatively young female participants with high levels of narcissism. Although the exhaustive CHAID results demonstrate that the most important variable is age, including the level of narcissism in the equation expands the literature and reveals the need for further research.

The results contribute to the understanding of online shopping addiction by identifying the significant role of narcissism, age, and gender. This sheds light on the complex interplay between individual characteristics and online shopping behavior. The results suggest a need to refine existing theoretical models of online shopping addiction to incorporate the nuanced effects of narcissism, age, and gender. This underscores the importance of considering individual differences in conceptualizing and addressing addictive behaviors in the online shopping context. By highlighting that younger female participants with higher levels of narcissism are particularly susceptible to online shopping addiction, the study provides insights into vulnerable demographic groups. This can inform targeted interventions and preventive measures tailored to these populations.

There are no studies in the literature examining the relationship between online shopping addiction and narcissism. Online shopping addiction has increased rapidly all over the world and leads to negative effects in addition to positive effects on individuals. Literature studies have elucidated that individuals with compulsive shopping addiction harm both themselves and the people around them. Therefore, studies on this subject are crucial. Furthermore, various promotional and educational activities can be carried out by using advertisements, banners, or brochures to raise awareness in individuals on issues such as spending a long time on the internet and the frequency of online shopping and to inform them about online shopping addiction.

It may be suggested to conduct studies on online shopping addiction with different sample groups and different variables. Moreover, it is thought that the results will provide important clues in coping with shopping addiction. In the study, when online shopping addiction was compared according to the gender variable, it was seen that the average of women was significantly higher than that of men. Based on this finding, a study can be conducted on the question of what factors lead women to online shopping addiction.

The identification of younger female individuals with high narcissism levels as a high-risk group for online shopping addiction suggests the need for tailored intervention strategies. These may include targeted education programs, counseling services, or online support groups aimed at addressing underlying narcissistic tendencies and promoting healthier online shopping habits. Based on the findings, prevention programs targeting individuals at risk, particularly young females exhibiting narcissistic traits, could be developed and implemented. These programs may focus on enhancing self-awareness, coping skills, and impulse control to mitigate the risk of developing problematic online shopping behaviors. Retailers can also play a role in mitigating online shopping addiction by implementing responsible marketing practices and providing resources for promoting balanced consumption. Strategies such as transparent pricing, limiting promotional tactics, and offering tools for managing online spending could help mitigate the risk of excessive shopping behavior among vulnerable individuals.